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IP disclosure and ownership checklist for AI-generated code

In one sentence: turn the AI code ownership / liability / IP principle into a checklist you can tick item by item before shipping. Don't reflexively treat AI-generated code as a "clean, exclusively ownable, protected" asset โ€” it may be without copyright protection yet still infringing. Walk this before you merge or distribute.

Checklist: walk this before treating AI code as an assetโ€‹

License and contamination (no scenario is exempt)

  • CI runs a license scan: no copyleft (GPL / AGPL) dependency drags its viral obligations into your closed-source code.
  • A similarity / provenance check has run: this code doesn't reproduce, verbatim, a copyrighted snippet from the training data (see License / IP contamination).

Copyrightability (when you mean to claim exclusivity / treat it as a core asset)

  • This code involved substantial human authorship (a person made creative design decisions, choices, and modifications) โ€” not just "handed the AI a prompt and let it generate the whole thing," which can fall into the "no copyright" gray zone.
  • You know which parts can be claimed under copyright and which can't, and you aren't mistaking the "unprotected" parts for a moat.

Ownership and liability (in writing)

  • The attribution / ownership of AI-assisted code is settled (who owns it).
  • How defect / infringement liability is allocated is settled (it defaults to the party that ships, not the tool vendor).
  • For high-sensitivity IP: you assessed "whether and how far to use AI generation here" up front, rather than discovering after the fact that your ownership won't hold up.

How to use itโ€‹

  • The two license items are hard gates: even if you don't plan to claim copyright and won't distribute externally, pulling restricted code or a copyleft dependency in verbatim still leaves you liable โ€” run both scans in every scenario.
  • Tighten copyrightability and ownership by scenario: an internal one-off script can keep it light; anything headed into a product, claimed as exclusive, or distributed should walk the whole list.
  • Wire this checklist into your release flow / legal review as a gate for "before AI-generated code ships."

When to use thisโ€‹

A good fit whenโ€‹

  • You're merging AI-generated code into a product, distributing it externally, or treating it as a company's exclusive asset.
  • Your team / legal needs a written checklist of "what to check before AI code ships."

Not a fit whenโ€‹

  • An internal, one-off, non-distributed script with no copyright claim โ€” just walk the two "license and contamination" items; the rest can be skipped.
  • You explicitly plan to open-source it / place it in the public domain โ€” the lack of copyright protection is no loss, so skip the copyrightability items; but license contamination still needs checking.

Replace before usingโ€‹

  • This checklist is not legal advice: it draws on the U.S. Copyright Office's 2025 guidance and Doe v. GitHub, and conclusions may differ in other jurisdictions โ€” verify with your local jurisdiction and company counsel before acting.
  • Swap "license scan / similarity check" for the tools you actually use (e.g., SCA / SBOM tools, a code-similarity service).
  • Wire the attribution / ownership / liability items into your company's AI-use policy and contract templates.